The investigation of asthma phenotypes

Siroux, Valérie; Garcia‐Aymerich, Judith

doi:10.1097/aci.0b013e32834a955a

Cited by 26 publications

(23 citation statements)

References 27 publications

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“…Compared to this simple approach, the benefits of multidimensional approaches in addressing a heterogeneous disease (with regards to its etiology, pathobiology or treatments) have been demonstrated for other respiratory/allergic disorders, such as asthma, wheezing illness of childhood, or atopy. [18–21] Bronchiolitis heterogeneity could reflect the existence of several underlying phenotypes, or clinically meaningful profiles, that have different roles in the development of childhood asthma. [3,5] However, to date, no consensus has emerged regarding the definition of subgroups of children with bronchiolitis who may respond differently to medications and/or have different short- or long-term outcomes.…”

Section: Introductionmentioning

confidence: 99%

A clustering approach to identify severe bronchiolitis profiles in children

Dumas

Mansbach

Jartti

et al. 2016

Thorax

121

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Objective Although bronchiolitis is generally considered a single disease, recent studies suggest heterogeneity. We aimed to identify severe bronchiolitis profiles using a clustering approach. Methods We analyzed data from two prospective, multi-center cohorts of children younger than 2 years hospitalized with bronchiolitis, one in the U.S. (2007–2010 winter seasons, n=2,207) and one in Finland (2008–2010 winter seasons, n=408). Severe bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical factors and viral etiology. Results In the U.S. study, four profiles were identified. Profile A (12%) was characterized by history of wheezing and eczema, wheezing at the ED presentation and rhinovirus infection. Profile B (36%) included children with wheezing at the ED presentation, but, in contrast to profile A, most did not have history of wheezing or eczema; this profile had the largest probability of RSV-infection. Profile C (34%) was the most severely ill group, with longer hospital stay and moderate-to-severe retractions. Profile D (17%) had the least severe illness, including non-wheezing children with shorter length-of-stay. Two of these profiles (A and D) were replicated in the Finnish cohort; a third group (“BC”) included Finnish children with characteristics of profiles B and/or C in the U.S. population. Conclusion Several distinct clinical profiles (phenotypes) were identified by a clustering approach in two multicenter studies of children hospitalized for bronchiolitis. The observed heterogeneity has important implications for future research on the etiology, management and long-term outcomes of bronchiolitis, such as future risk of childhood asthma.

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Section: Introductionmentioning

confidence: 99%

A clustering approach to identify severe bronchiolitis profiles in children

Dumas

Mansbach

Jartti

et al. 2016

Thorax

121

View full text Add to dashboard Cite

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“…The next step will be to refine the characteristics of these phenotypes adding well-known aetiological factors such as occupational exposure, nasal polyposis and aspirin sensitivity into the models. Furthermore, the stability of the asthma phenotypes has to be further explored [103]. In children, the clinical expression of the disease varies over time and novel wheezing phenotypes have been identified on the basis of longitudinal follow-up data [104].…”

Section: Smoking-related Asthmamentioning

confidence: 99%

Adult-onset asthma: is it really different?

Nijs¹,

Venekamp²,

Bel³

2013

Eur Respir Rev

248

214

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Asthma that starts in adulthood differs from childhood-onset asthma in that it is often non-atopic, more severe and associated with a faster decline in lung function.Understanding of the underlying mechanism of adult-onset asthma and identification of specific phenotypes may further our understanding of pathophysiology and treatment response, leading to better targeting of both existing and new approaches for personalised management. Pivotal studies in past years have led to sustained progress in many areas, ranging from risk factors for development, identification of different phenotypes, and introduction of new therapies.This review highlights and discusses literature on adult-onset asthma, with special focus on the differences from childhood-onset asthma, risk factors for development, phenotypes of adultonset asthma and new approaches for personalised management.

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“…Such results provided the first evidence for a genetic heterogeneity of asthma phenotypes. Unsupervised models aiming to identify homogeneous subgroups of subjects have been applied to unravel the phenotypic heterogeneity of asthma [7]. In adult asthma, these studies led to the identification of asthma phenotypes that exhibited differences in clinical response to treatment, in clinical, physiological and inflammatory parameters and in health-related quality of life [5,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Genetic heterogeneity of asthma phenotypes identified by a clustering approach

et al. 2013

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The aim of the study was to identify genetic variants associated with refined asthma phenotypes enabling multiple features of the disease to be taken into account.Latent class analysis (LCA) was applied in 3001 adults ever having asthma recruited in the frame of three epidemiological surveys (the European Community Respiratory Health Survey (ECRHS), the Swiss Study on Air Pollution and Lung Disease in Adults (SAPALDIA) and the Epidemiological Study on the Genetics and Environment of Asthma (EGEA)). 14 personal and phenotypic characteristics, gathered from questionnaires and clinical examination, were used. A genome-wide association study was conducted for each LCA-derived asthma phenotype, compared to subjects without asthma (n=3474).The LCA identified four adult asthma phenotypes, mainly characterised by disease activity, age of asthma onset and atopic status. Associations of genome-wide significance (p<1.25×10−7) were observed between “active adult-onset nonallergic asthma” and rs9851461 flankingCD200(3q13.2) and between “inactive/mild nonallergic asthma” and rs2579931 flankingGRIK2(6q16.3). Borderline significant results (2.5×10−7<p<8.2×10−7) were observed between three single nucleotide polymorphisms (SNPs) in theALCAMregion (3q13.11) and “active adult-onset nonallergic asthma”. These results were consistent across studies. 15 SNPs identified in previous genome-wide association studies of asthma have been replicated with at least one asthma phenotype, most of them with the “active allergic asthma” phenotype.Our results provide evidence that a better understanding of asthma phenotypic heterogeneity helps to disentangle the genetic heterogeneity of asthma.

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The investigation of asthma phenotypes

Cited by 26 publications

References 27 publications

A clustering approach to identify severe bronchiolitis profiles in children

A clustering approach to identify severe bronchiolitis profiles in children

Adult-onset asthma: is it really different?

Genetic heterogeneity of asthma phenotypes identified by a clustering approach

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